The creation of large-surface composition images (also called panoramic images) of the eye fundus is necessary for the diagnosis and monitoring of various eye diseases, for example, diabetic retinopathy. Due to optical and physiological limitations, the imaging of solid angles >50° is not possible with standard fundus cameras. Therefore, in order to create composition images, which cover a greater solid angle, overlapping partial images are taken and combined accordingly. Thereby, the images must be associated with each other in a geometrically exact fashion; furthermore, very often a matching of intensities and/or colors is required. Position and sequence of the partial images are partially predefined through clinical protocols (e.g., ETDRS=Early Treatment Diabetic Retinopathy Study).
In analog fundus photography, prints are cut from partial images, shifted and rotated against each other and glued together to form a composition image. Thereby, the technician attempts to overlap with best possible accuracy prominent points (mostly blood vessels of the eye fundus with characteristic curves or branches). This method is time-consuming, limited to translatory and rotational corrections, and of limited reproducibility. Due to varying exposure conditions, the borders of the partial images are boosted which makes the diagnosis of composition results more difficult.
If partial images are available in electronic form, transformations can be determined through manual marking of corresponding points in different partial images, and which produce an ideal composition (generally, in the sense of minimizing the residual flaws at the corresponding points after executing the transformation).
Said methods require a significant and time-consuming interaction by the technician. First, a rough arrangement of the partial images must be determined. Then, prominent points (“landmarks,” e.g., blood vessel branches) must be determined in every partial image and the corresponding points marked in at least one other partial image. Very often, the technician must switch between different levels of resolution of the representation. Through analysis of the corresponding points, various geometric transformations can be calculated, depending on the number of landmarks. Superimposition of the appropriately transformed partial images results in a (digital) composition image.
It has also been suggested that the corresponding landmarks be determined automatically (i.e., computer-assisted). In the article by Chanwimaluang et al., “Hybrid Retinal Image Registration” IEEE Transactions on Information Technology in Biomedicine 10(I): 129-142 (2006), corresponding landmarks, based on landmark candidates of a partial image, are determined in other partial images on the basis of different similarity measures and statistical analyses.
The rest of the process (calculation of ideal transformations, superimposition of partial images) is analog to the above described semiautomatic method. In order to reduce the computational effort, a two-step method is suggested, whereby the shift between two images is calculated before the control point registration, which is achieved by means of the transformation and various optimization techniques.
Said method is disadvantageous due to the poor robustness, since the detected landmarks must meet criteria, which are influenced by the imaging quality (focusing, exposure) and the framing. Furthermore, an even distribution of the specific landmarks on the partial images is not guaranteed. As a result, only individual (structurally complex) areas of the image may be included in the determination of the transformation and, e.g., a scaling in the periphery may not be included. The number of landmarks used for determining the transformation is image-dependent and, therefore, generally unpredictable.
Other suggested methods, e.g., the reconstruction of the blood vessels of the eye fundus in the form of a geometric tree require an extraordinary amount of calculations (e.g., Chanwimaluang et al., “An efficient blood vessel detection algorithm for retinal images using local entropy thresholding,” ISCAS (5) 2003: 21-24).
The Japanese patent application JP 11-332832 suggests that the imaging parameters, such as direction and magnification, of every partial image are saved and, therefore, produce panoramic images analytically and without the use of the image content.
It is known, e.g., from U.S. Pat. No. 4,715,703, to provide a fundus camera with an aperture mask (field stop) in order to mask off unwanted scattered light.
In US patent application 2004/0254477, it is suggested that a virtual field stop, instead of a real field stop, is defined through user input of the diameter, and to manipulate the grey values and/or the pixels of the (rectangular) digital image in such a way that the impression of a picture with field stop is created.